Browsing Wirtschaftswissenschaftliche Fakultät by Advisor "Kneib, Thomas Prof. Dr."
Now showing items 1-7 of 7
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Estimating and evaluating mixed and semiparametric models with statistical and deep learning methods
(2023-09-11)Semiparametric models are well-established, versatile and effective statistical models for analysing complex data by combining both parametric and non-parametric components and are used in a wide range of applications and ... -
Semi-Parametric Distributional Regression in Forestry and Ecology
(2023-08-10)Recent advances in machine learning software, such as automatic differentiation and just-in-time (JIT) compilation, have significantly changed machine learning research. They have accelerated model development and contributed ... -
The visualization, unbiased estimation and interpretation of distributional regression models
(2022-06-20)Distributional regression represents a modern approach to regression modeling that yields the ability to simultaneously connect multiple parameters beyond the mean of any parametric response distribution to structured ... -
It's Time: Poverty, Inequality and Sustainability beyond the Mean
(2022-03-08)Differences in time allocation enlighten patterns of gendered poverty. This thesis disentangles the interlinked nature of deprivations in leisure time and income as well as income inequality and carbon emissions. Regressions ... -
Digitalisierung im Personenverkehr
(2020-06-05)The effects of demographic change and lack of acceptance pose some of the main problems for public transport infrastructure in rural areas in developed countries. In developing countries, however, there is a need to ... -
Causality, Prediction, and Replicability in Applied Statistics: Advanced Models and Practices
(2019-07-11)Statistical tools to analyze research data are widely applied in many scientific disciplines and the need for adequate statistical models and sound statistical analyses is apparent. This thesis addresses limitations in ... -
Effect Separation in Regression Models with Multiple Scales
(2017-06-12)Confounding problems in regression analysis arise when one or more third variables are simultaneously associated with both the covariates and the response variables under consideration. Even when these confounders are ...